Comparison of whole genome sequencing typing tools for the typing of Belgian Legionella pneumophila outbreaks isolates.

IF 3.7 3区 医学 Q2 INFECTIOUS DISEASES
Fedoua Echahidi, Subin Park, Alaeddine Meghraoui, Florence Crombé, Oriane Soetens, Denis Piérard, Benoit Prevost, Ingrid Wybo, Charlotte Michel
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Abstract

Whole genome sequencing (WGS) marks a turning point for outbreak investigations for microorganisms related to public health matters, like Legionella pneumophila (Lp). Here, we evaluated the available Lp WGS typing tools for isolates of previously documented Belgian outbreaks, as well as small groups of related and non-related isolates. One reference strain and 77 clinical and environmental isolates were evaluated. Seven isolates belong to a Sequence Type (ST) 36 outbreak in 1999 and sixteen (ten clinical, two matching environmental and four non-related controls) belong to another ST1 outbreak in 1985-1987. The remaining isolates belong to small groups of related and non-related isolates of diverse ST's. WGS was performed and data were analysed using whole genome (wg) and core genome (cg) multilocus sequence typing (MLST) with "Ridom SeqSphere + " (cgMLST), "Applied Maths-Bionumerics" (wgMLST) and the 50 loci cgMLST (CDC/ESGLI_ESCMID). Results of the three tools were concordant with the traditional Sequence Based Typing (SBT). The known outbreaks and small clusters could be detected and clear discrimination of ST1 non-related isolates was obtained. In addition, the 50 loci cgMLST allowed to classify the isolates into subtypes because almost all the 50 genes could be called in all the analysed isolates, which was not achieved by the other tools. This is a big advantage in terms of standardisation and comparison between laboratories for future epidemiological investigations. WGS allowed to analyse a large volume of samples and generated more accurate conclusions for outbreak investigations compared to other typing methods due to its higher discriminatory power and throughput.

比利时嗜肺军团菌暴发分离株全基因组测序分型工具的比较。
全基因组测序(WGS)标志着与嗜肺军团菌(Lp)等公共卫生问题相关的微生物暴发调查的一个转折点。在这里,我们评估了现有的Lp WGS分型工具,用于先前记录的比利时疫情分离株,以及小群相关和非相关分离株。鉴定了1株参考菌株和77株临床和环境分离菌株。7株分离株属于1999年序列型(ST) 36暴发,16株(10株为临床暴发,2株为环境暴发,4株为非相关对照)属于1985-1987年的另一次ST1暴发。剩下的分离株属于不同ST的相关和非相关分离的小群体。采用全基因组(wg)和核心基因组(cg)多位点序列分型(MLST),采用“Ridom SeqSphere +”(cgMLST)、“Applied math - bionumerics”(wgMLST)和50个位点的cgMLST (CDC/ESGLI_ESCMID)进行数据分析。这三种工具的结果与传统的序列分型(SBT)一致。可以检测到已知的暴发和小聚集性,并对ST1非相关分离株进行了明确的区分。此外,50个基因座cgMLST允许将分离物分类为亚型,因为几乎所有50个基因都可以在所有分析的分离物中被调用,这是其他工具无法实现的。这在标准化和实验室之间的比较方面为今后的流行病学调查提供了很大的优势。与其他分型方法相比,WGS能够分析大量样本,并为疫情调查得出更准确的结论,因为它具有更高的区分能力和吞吐量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
10.40
自引率
2.20%
发文量
138
审稿时长
1 months
期刊介绍: EJCMID is an interdisciplinary journal devoted to the publication of communications on infectious diseases of bacterial, viral and parasitic origin.
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